A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 8 Issue 10
Oct.  2021

IEEE/CAA Journal of Automatica Sinica

• JCR Impact Factor: 6.171, Top 11% (SCI Q1)
CiteScore: 11.2, Top 5% (Q1)
Google Scholar h5-index: 51， TOP 8
Turn off MathJax
Article Contents
Xianggui Guo, Dongyu Zhang, Jianliang Wang and Choon Ki Ahn, "Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks," IEEE/CAA J. Autom. Sinica, vol. 8, no. 10, pp. 1644-1656, Oct. 2021. doi: 10.1109/JAS.2021.1004132
 Citation: Xianggui Guo, Dongyu Zhang, Jianliang Wang and Choon Ki Ahn, "Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks," IEEE/CAA J. Autom. Sinica, vol. 8, no. 10, pp. 1644-1656, Oct. 2021.

# Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks

##### doi: 10.1109/JAS.2021.1004132
Funds:  This work was supported by the National Natural Science Foundation of China (61773056), the Scientific and Technological Innovation Foundation of Shunde Graduate School, University of Science and Technology Beijing (USTB) (BK19AE018), and the Fundamental Research Funds for the Central Universities of USTB (FRF-TP-20-09B, 230201606500061, FRF-DF-20-35, FRF-BD-19-002A). The work of J. L. Wang was supported by Zhejiang Natural Science Foundation (LD21F030001). The work of C. K. Ahn was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and Information and Communications Technology) (NRF-2020R1A2C1005449)
• This paper investigates the event-triggered security consensus problem for nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks over an undirected graph. A novel adaptive memory observer-based anti-disturbance control scheme is presented to improve the observer accuracy by adding a buffer for the system output measurements. Meanwhile, this control scheme can also provide more reasonable control signals when DoS attacks occur. To save network resources, an adaptive memory event-triggered mechanism (AMETM) is also proposed and Zeno behavior is excluded. It is worth mentioning that the AMETM’s updates do not require global information. Then, the observer and controller gains are obtained by using the linear matrix inequality (LMI) technique. Finally, simulation examples show the effectiveness of the proposed control scheme.

•  [1] J. J. Cui, Y. W. Liu, and A. Nallanathan, “Multi-agent reinforcement learning-based resource allocation for UAV networks,” IEEE Trans. Wireless Commun., vol. 19, no. 2, pp. 729–743, Feb. 2020. [2] D. Chowdhury and H. K. Khalil, “Practical synchronization in networks of nonlinear heterogeneous agents with application to power systems,” IEEE Trans. Autom. Control, vol. 66, no. 1, pp. 184–198, Jan. 2021. [3] Y. Kikuya, S. M. Dibaji, and H. Ishii, “Fault-tolerant clock synchronization over unreliable channels in wireless sensor networks,” IEEE Trans. Control Netw. Syst., vol. 5, no. 4, pp. 1551–1562, Dec. 2018. [4] M. B. Khalkhali, A. Vahedian, and H. S. Yazdi, “Multi-target state estimation using interactive kalman filter for multi-vehicle tracking,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 3, pp. 1131–1144, Mar. 2020. [5] L. W. An and G. H. Yang, “Decentralized adaptive fuzzy secure control for nonlinear uncertain interconnected systems against intermittent DoS attacks,” IEEE Trans. Cybern., vol. 49, no. 3, pp. 827–838, Mar. 2019. [6] C. Deng and C. Y. Wen, “Distributed resilient observer-based faulttolerant control for heterogeneous multiagent systems under actuator faults and DoS attacks,” IEEE Trans. Control Netw. Syst., vol. 7, no. 3, pp. 1308–1318, Sep. 2020. [7] Y. M. Wu and X. X. He, “Secure consensus control for multiagent systems with attacks and communication delays,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 136–142, Jan. 2017. [8] D. Zhang, G. Feng, Y. Shi, and D. Srinivasan, “Physical safety and cyber security analysis of multi-agent systems: a survey of recent advances,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 319–333, Feb. 2021. [9] W. L. He, Z. K. Mo, Q. -L. Han, and F. Qian, “Secure impulsive synchronization in Lipschitz-type multi-agent systems subject to deception attacks,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1326–1334, Sep. 2020. [10] X. Huang and J. X. Dong, “Reliable leader-to-follower formation control of multiagent systems under communication quantization and attacks,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 50, no. 1, pp. 89–99, Jan. 2020. [11] G. Franze, F. Tedesco, and D. Famularo, “Resilience against replay attacks: A distributed model predictive control scheme for networked multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 628–640, Mar. 2021. [12] C. J. Zhou, B. W. Hu, Y. Shi, Y. C. Tian, X. Li, and Y. Zhao, “A unified architectural approach for cyberattack-resilient industrial control systems,” Proc. IEEE, vol. 109, no. 4, pp. 517–541, Apr. 2021. [13] Y. Wan, G. H. Wen, X. H. Yu, and T. W. Huang, “Distributed consensus tracking of networked agent systems under Denial-of-Service attacks,” IEEE Trans. Syst., Man, Cybern., Syst., to be published, Jan. 2020. [14] E. Mousavinejad, F. W. Yang, Q. L. Han, X. H. Ge, and L. Vlacic, “Distributed cyber attacks detection and recovery mechanism for vehicle platooning,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 9, pp. 3821–3834, Sep. 2020. [15] C. De Persis and P. Tesi, “Input-to-state stabilizing control under denialof-service,” IEEE Trans. Autom. Control, vol. 60, no. 11, pp. 2930–2944, Nov. 2015. [16] T. Y. Zhang and D. Ye, “Distributed event-triggered control for multiagent systems under intermittently random denial-of-service attacks,” Inf. Sci., vol. 542, pp. 380–390, Jan. 2021. [17] Z. Feng and G. Q. Hu, “Secure cooperative event-triggered control of linear multiagent systems under DoS attacks,” IEEE Trans. Control Syst. Technol., vol. 28, no. 3, pp. 741–752, May 2020. [18] Y. Xu, M. Fang, Z. G. Wu, Y. J. Pan, M. Chadli, and T. W. Huang, “Input-based event-triggering consensus of multiagent systems under denial-of-service attacks,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 50, no. 4, pp. 1455–1464, Apr. 2020. [19] Y. Yang, Y. F. Li, D. Yue, Y. C. Tian, and X. H. Ding, “Distributed secure consensus control with event-triggering for multiagent systems under DoS attacks,” IEEE Trans. Cybern., vol. 51, no. 6, pp. 2916–2928, Jun. 2021. [20] L. Zhao and G. H. Yang, “Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks,” Inf. Sci., vol. 526, pp. 39–53, Jul. 2020. [21] J. L. Liu, T. T. Yin, D. Yue, H. R. Karimi, and J. D. Cao, “Event-based secure leader-following consensus control for multiagent systems with multiple cyber attacks,” IEEE Trans. Cybern., vol. 51, no. 1, pp. 162–173, Jan. 2021. [22] X. G. Guo, X. Fan, J. L. Wang, and J. H. Park, “Event-triggered switching-type fault detection and isolation for fuzzy control systems under DoS attacks,” IEEE Trans. Fuzzy Syst., to be published, Sep. 2020. [23] W. C. Zou, C. K. Ahn, and Z. R. Xiang, “Fuzzy-approximation-based distributed fault-tolerant consensus for heterogeneous switched nonlinear multiagent systems,” IEEE Trans. Fuzzy Syst., to be published, Jul. 2020. [24] X. G. Guo, J. L. Wang, and F. Liao, “Adaptive quantised H∞ observer-based output feedback control for non-linear systems with input and output quantisation,” IET Control Theory Appl., vol. 11, no. 2, pp. 263–272, Jan. 2017. [25] S. L. Hu, D. Yue, Q. L. Han, X. P. Xie, X. L. Chen, and C. X. Dou, “Observer-based event-triggered control for networked linear systems subject to denial-of-service attacks,” IEEE Trans. Cybern., vol. 50, no. 5, pp. 1952–1964, May 2020. [26] Z. Y. Wu, H. D. Mo, J. L. Xiong, and M. Xie, “Adaptive event-triggered observer-based output feedback ${\cal{L}}_{\infty }$ load frequency control for networked power systems” IEEE Trans. Ind. Inf., vol. 16, no. 6, pp. 3952–3962, Jun. 2020. [27] Y. Wu, H. Liang, Y. Zhang, and C. K. Ahn, “Cooperative adaptive dynamic surface control for a class of high-order stochastic nonlinear multi-agent systems,” IEEE Trans. Cybern. to be published, May 2020. [28] X. G. Guo, J. L. Wang, F. Liao, and R. S. H. Teo, “Distributed adaptive sliding mode control strategy for vehicle-following systems with nonlinear acceleration uncertainties,” IEEE Trans. Veh. Technol., vol. 66, no. 2, pp. 981–991, Feb. 2017. [29] I. Furtat, E. Fridman, and A. Fradkov, “Disturbance compensation with finite spectrum assignment for plants with input delay,” IEEE Trans. Autom. Control, vol. 63, no. 1, pp. 298–305, Jan. 2018. [30] Y. Yuan, Z. D. Wang, and L. Guo, “Event-triggered strategy design for discrete-time nonlinear quadratic games with disturbance compensations: the noncooperative case,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 48, no. 11, pp. 1885–1896, Nov. 2018. [31] X. G. Guo, X. Fan, and C. K. Ahn, “Adaptive event-triggered fault detection for interval type-2 T-S fuzzy systems with sensor saturation,” IEEE Trans. Fuzzy Syst., to be published, May 2020. [32] W. Y. Xu, D. W. C. Ho, J. Zhong, and B. Chen, “Event/Self-triggered control for leader-following consensus over unreliable network with DoS attacks,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 10, pp. 3137–3149, Oct. 2019. [33] D. Ye, M. M. Chen, and H. J. Yang, “Distributed adaptive eventtriggered fault-tolerant consensus of multiagent systems with general linear dynamics,” IEEE Trans. Cybern., vol. 49, no. 3, pp. 757–767, Mar. 2019. [34] B. Cheng and Z. K. Li, “Fully distributed event-triggered protocols for linear multiagent networks,” IEEE Trans. Autom. Control, vol. 64, no. 4, pp. 1655–1662, Apr. 2019. [35] S. L. Hu, D. Yue, X. P. Xie, X. L. Chen, and X. X. Yin, “Resilient event-triggered controller synthesis of networked control systems under periodic DoS jamming attacks,” IEEE Trans. Cybern., vol. 49, no. 12, pp. 4271–4281, Dec. 2019. [36] E. G. Tian, K. Y. Wang, X. Zhao, S. B. Shen, and J. L. Liu, “An improved memory-event-triggered control for networked control systems,” J. Franklin Inst., vol. 356, no. 13, pp. 7210–7223, Sep. 2019. [37] K. Y. Wang, E. G. Tian, S. B. Shen, L. N. Wei, and J. L. Zhang, “Input-output finite-time stability for networked control systems with memory event-triggered scheme,” J. Franklin Inst., vol. 356, no. 15, pp. 8507–8520, Oct. 2019. [38] C. L. Liu, L. Shan, Y. Y. Chen, and Y. Zhang, “Average-consensus filter of first-order multi-agent systems with disturbances,” IEEE Trans. Circuits Syst.,Ⅱ,Exp. Briefs, vol. 65, no. 11, pp. 1763–1767, Nov. 2018. [39] X. D. Wang, Z. Y. Fei, T. Wang, and L. Yang, “Dynamic event-triggered actuator fault estimation and accommodation for dynamical systems,” Inf. Sci., vol. 525, pp. 119–133, Jul. 2020. [40] B. H. Wang, W. S. Chen, J. C. Wang, B. Zhang, Z. Q. Zhang, and X. G. Qiu, “Accurate cooperative control for multiple leaders multiagent uncertain systems: a two-layer node-to-node communication framework,” IEEE Trans. Ind. Inf., vol. 14, no. 6, pp. 2395–2405, Jun. 2018. [41] Y. B. Gao, J. X. Liu, G. H. Sun, M. Liu, and L. G. Wu, “Fault deviation estimation and integral sliding mode control design for Lipschitz nonlinear systems,” Syst. Control Lett., vol. 123, pp. 8–15, Jan. 2019. [42] A. ur Rehman, M. Rehan, N. Iqbal, and C. K. Ahn, “LPV scheme for robust adaptive output feedback consensus of lipschitz multiagents using lipschitz nonlinear protocol,” IEEE Trans. Syst., Man, Cybern., Syst., to be published, Jan. 2020. [43] Y. Xu, M. Fang, P. Shi, and Z. G. Wu, “Event-based secure consensus of mutiagent systems against DoS attacks,” IEEE Trans. Cybern., vol. 50, no. 8, pp. 3468–3476, Aug. 2020. [44] R. N. Yang and W. X. Zheng, “Output-based event-triggered predictive control for networked control systems,” IEEE Trans. Ind. Electron., vol. 67, no. 12, pp. 10631–10640, Dec. 2020.

### Catalog

###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

Figures(8)  / Tables(2)